Gaussian approximation based mixture reduction for joint channel estimation and detection in MIMO systems

Y Jia, C Andrieu, RJ Piechocki, M Sandell

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1 Citation (Scopus)
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A novel Gaussian approximation based mixture reduction algorithm is proposed for semi-blind joint channel tracking and symbol detection for spatial multiplexing multiple-input multiple-output (MIMO) systems with frequency-flat time-selective channels. The proposed algorithm is based on a modified sequential Gaussian approximation detector (SGA) which takes into account channel uncertainty, and the first order generalized pseudo-Bayesian (GPB1) channel estimator. Simulation results show that the proposed algorithm performs better than the conventional and computationally expensive decision-directed method with Kalman filter based channel estimation and a posteriori probability (APP) symbol detection.
Original languageEnglish
Pages (from-to)2384 - 2389
Number of pages6
JournalIEEE Transactions on Wireless Communications
Issue number77
Publication statusPublished - Jul 2007

Bibliographical note

Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Rose publication type: Journal article

Sponsorship: This work was supported by Toshiba Research Europe Ltd (Bristol), UK.

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  • joint estimation and detection
  • MIMO systems
  • multiple model estimation
  • multiuser detection
  • time-varying channels

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